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Leachate detection via statistical analysis of electrical resistivity and induced polarization data at a waste disposal site (Northern Israel)

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Abstract

Landfill site is an intensely heterogeneous medium, in which application of 2-D geophysical techniques frequently does not enable its accurate examination due to the lack of correlation between different geophysical profiles. The study was aimed to eliminate such difficulty. Hereafter, the leachate detection methodology is presented including 2-D smoothness-constrained inversion of geoelectrical raw data collected in situ, the inverted data normalization and statistical examination. To eradicate influence of high heterogeneity of the landfill body, the generalized statistical model of the entire site was created including the likelihood analysis of the entire normalized data set. Three geoelectrical parameters were involved in the analysis: inversed electrical resistivity, inversed chargeability (IP) and the ratio of inversed chargeability-to-inversed electrical resistivity (IP/Res). The study was combined with the synthetic modeling, the analysis of bulk versus fluid electrical resistivity relationship and test borehole drillings. Such generalized analysis ensures independency of the results from the locality of sampling/measurements. It was shown that leachate detection can be correctly performed utilizing the IP/Res ratio while the anomaly’s likelihood is higher than 90%.

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Authors and Affiliations

  1. The Sami Shamoon College of Engineering, Ashdod Campus, Ashdod, Israel

    Vladimir Frid

  2. Tel-Aviv University, Tel-Aviv, Israel

    Itay Sharabi

  3. Ben Gurion University of the Negev, Beer Sheva, Israel

    Michael Frid

  4. Isotop Ltd, Gedera, Israel

    Arie Averbakh

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  1. Vladimir Frid
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  2. Itay Sharabi
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  3. Michael Frid
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  4. Arie Averbakh
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Correspondence to Vladimir Frid.

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Frid, V., Sharabi, I., Frid, M. et al. Leachate detection via statistical analysis of electrical resistivity and induced polarization data at a waste disposal site (Northern Israel). Environ Earth Sci 76, 233 (2017). https://doi.org/10.1007/s12665-017-6554-4

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